Tools to Choose For RNA-Seq Normalization?

Question

[Briony]

Hi,

Thank you for all the help in advance. I searched a lot papers but none of them explained my question clearly, so I guess here is a great place I can get help.

My question is what software would you use to get the best performance for the following distinct goals in RNA-seq analysis?

1. normalization of transcript abundance when a small number of changes (~ 2 fold) are expected.
2. normalization when dramatic changes in the expression of many genes (~100 fold or greater) are expected.

Answer 1

[Ming Tommy Tang]

For differential expression analysis, people usually use DESeq and EdgeR. You need to read the papers to see the statistical models behind that.

[BioinfGuru]

DESEQ2 has great support on bioconductor and I believe is more recently updated, but I hope you have replicates.

Answer 2

[Manvendra Singh]

I would say DESeq for both

This is a very nice paper to answer your question; you can just go through it and see this figure.